Real-time video analytics on small autonomous drones poses several difficult challenges at the intersection of wireless bandwidth, processing capacity, energy consumption, result accuracy, and timeliness of results. In response to these challenges, we describe four strategies to build an adaptive computer vision pipeline for search tasks in domains such as

The generation of high-quality training data has become the key bottleneck in the use of deep learning across many domains. We describe Eureka, an interactive system that leverages edge computing and early discard to greatly improve the productivity of experts in the construction of a labeled data set. Our experimental

Recently, edge computing has emerged as a promising computing paradigm to meet stringent quality-of-service requirements of an increasing number of latency-sensitive applications. The core principle of edge computing is to bring the capability of cloud computing in close proximity to mobile devices, sensors, actuators, connected things and end users, thereby

Disk Tray AssemblyIn collaboration with the company inwinSTACK, we created a Gabriel application for training a new worker in disk tray assembly for a desktop. This demo was shown live at the Computex 2018 show in Taiwan in June 2018. The application was created by Junjue Wang of CMU, and

Wearable cognitive assistance applications can provide guidance for many facets of a user’s daily life. This thesis targets the enabling of a new genre of such applications that require both heavy computation and very low response time on inputs from mobile devices. The core contribution of this thesis is

6 course projectsThe Fall 2017 offering of 15-821/18-843 "Mobile and Pervasive Computing" course included several student projects based on cloudlets and wearable cognitive assistance. This is a YouTube playlist with videos of the student projects captured on the final day of class.

Accurate, up-to-date maps of transient traffic and hazards are invaluable to drivers, city managers, and the emerging class of self-driving vehicles. We present LiveMap, a scalable, automated system for acquiring, curating, and disseminating detailed, continually-updated road conditions in a region. LiveMap leverages in-vehicle cameras, sensors, and processors to crowd-source hazard

VM handoff enables rapid and transparent placement changes to executing code in edge computing use cases where the safety and management attributes of VM encapsulation are important. This versatile primitive offers the functionality of classic live migration but is highly optimized for the edge. Over WAN bandwidths ranging from 5